Exercise-Related Physical Activity Relates to Brain Volumes in 10,125 Individuals

BACKGROUND

The potential neuroprotective effects of regular physical activity on brain structure are unclear, despite links between activity and reduced dementia risk.

OBJECTIVE

To investigate the relationships between regular moderate to vigorous physical activity and quantified brain volumes on magnetic resonance neuroimaging.

METHODS

A total of 10,125 healthy participants underwent whole-body MRI scans, with brain sequences including isotropic MP-RAGE. Three deep learning models analyzed axial, sagittal, and coronal views from the scans. Moderate to vigorous physical activity, defined by activities increasing respiration and pulse rate for at least 10 continuous minutes, was modeled with brain volumes via partial correlations. Analyses adjusted for age, sex, and total intracranial volume, and a 5% Benjamini-Hochberg False Discovery Rate addressed multiple comparisons.

RESULTS

Participant average age was 52.98±13.04 years (range 18-97) and 52.3% were biologically male. Of these, 7,606 (75.1%) reported engaging in moderate or vigorous physical activity approximately 4.05±3.43 days per week. Those with vigorous activity were slightly younger (p < 0.00001), and fewer women compared to men engaged in such activities (p = 3.76e-15). Adjusting for age, sex, body mass index, and multiple comparisons, increased days of moderate to vigorous activity correlated with larger normalized brain volumes in multiple regions including: total gray matter (Partial R = 0.05, p = 1.22e-7), white matter (Partial R = 0.06, p = 9.34e-11), hippocampus (Partial R = 0.05, p = 5.96e-7), and frontal, parietal, and occipital lobes (Partial R = 0.04, p≤1.06e-5).

CONCLUSIONS

Exercise-related physical activity is associated with increased brain volumes, indicating potential neuroprotective effects.

T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease

Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

Snoring and risk of dementia: a prospective cohort and Mendelian randomization study

Background

The association between snoring, a very common condition that increases with age, and dementia risk is controversial. Snoring is linked to obstructive sleep apnoea and cardiometabolic conditions, both of which are associated with an increased risk of dementia. However, snoring also increases with body mass index (BMI), which in late life is linked to lower dementia risk, possibly due to metabolic changes during prodromal dementia.

Methods

The prospective cohort study used data from 450,027 UK Biobank participants with snoring measured at baseline (2006 - 2010), and followed up for dementia diagnosis (censored at 2022). Two-sample Mendelian randomization (MR) analysis used summary statistics for genome-wide association studies of Alzheimer's disease (AD) (n = 94,437; cases = 35,274) and snoring (n = 408,317; snorers = 151,011).

Results

During a median follow-up of 13.5 years, 7,937 individuals developed dementia. Snoring was associated with an 8% lower risk of all-cause dementia (hazard ratio [HR] 0.92; 95% confidence interval [CI] 0.88 to 0.97) and AD (HR 0.92; 95% CI 0.86 to 0.99). The association was stronger in older individuals, APOE ε4 allele carriers, and during shorter follow-up periods. MR analyses suggested no causal effect of snoring on AD, however, genetic liability to AD was associated with a lower risk of snoring. Multivariable MR indicated that the effect of AD on snoring was primarily driven by BMI.

Conclusions

The phenotypic association between snoring and lower dementia risk likely stems from reverse causation, with genetic predisposition to AD associated with reduced snoring. This may be driven by weight loss in prodromal AD.

Neuroinflammation: A Modifiable Pathway Linking Obesity, Alzheimer's disease, and Depression

Obesity, depression and Alzheimer's disease (AD) are three major interrelated modern health conditions with complex relationships. Early-life depression may serve as a risk factor for AD, while late-life depression may be a prodrome of AD. Depression affects approximately 23% of obese individuals, and depression itself raises the risk of obesity by 37%. Mid-life obesity independently increases AD risk, while late-life obesity, particularly metabolically healthy obesity, may offer protection against AD pathology. Chronic inflammation serves as a key mechanism linking obesity, AD, and depression, encompassing systemic inflammation from metabolic disturbances, immune dysregulation through the gut microbiome, and direct interactions with amyloid pathology and neuroinflammation. In this review, we explore the biological mechanisms of neuroinflammation in relation to obesity, AD, and depression. We assess the efficacy of therapeutic interventions targeting neuroinflammation and discuss current and future radiological imaging initiatives for studying neuroinflammation. By comprehending the intricate interplay among depression, obesity, and AD, especially the role of neuroinflammation, we can advance our understanding and develop innovative strategies for prevention and treatment.

Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study

Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRI-determined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman's partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology.

Benefits of a 12-Week Non-Drug "Brain Fitness Program" for Patients with Attention-Deficit/Hyperactive Disorder, Post-Concussion Syndrome, or Memory Loss

Background

Non-pharmacologic interventions can potentially improve cognitive function, sleep, and/or mood in patients with attention-deficit/hyperactive disorder (ADHD), post-concussion syndrome (PCS), or memory loss.

Objective

We evaluated the benefits of a brain rehabilitation program in an outpatient neurology practice that consists of targeted cognitive training, lifestyle coaching, and electroencephalography (EEG)-based neurofeedback, twice weekly (90 minutes each), for 12 weeks.

Methods

223 child and adult patients were included: 71 patients with ADHD, 88 with PCS, and 64 with memory loss (mild cognitive impairment or subjective cognitive decline). Patients underwent a complete neurocognitive evaluation, including tests for Verbal Memory, Complex Attention, Processing Speed, Executive Functioning, and Neurocognition Index. They completed questionnaires about sleep, mood, diet, exercise, anxiety levels, and depression-as well as underwent quantitative EEG-at the beginning and the end of the program.

Results

Pre-post test score comparison demonstrated that all patient subgroups experienced statistically significant improvements on most measures, especially the PCS subgroup, which experienced significant score improvement on all measures tested (p≤0.0011; d_z≥0.36). After completing the program, 60% to 90% of patients scored higher on cognitive tests and reported having fewer cognitive and emotional symptoms. The largest effect size for pre-post score change was improved executive functioning in all subgroups (ADHD d_z= 0.86; PCS d_z= 0.83; memory d_z= 1.09).

Conclusion

This study demonstrates that a multimodal brain rehabilitation program can have benefits for patients with ADHD, PCS, or memory loss and supports further clinical trials in this field.

Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitoring AD progression. However, atrophy patterns are complex and vary by patient. To address this issue, researchers have made efforts to develop more concise metrics that can summarize AD-specific atrophy. Many of these methods can be difficult to interpret clinically, hampering adoption. In this study, we introduce a novel index which we call an "AD-NeuroScore," that uses a modified Euclidean-inspired distance function to calculate differences between regional brain volumes associated with cognitive decline. The index is adjusted for intracranial volume (ICV), age, sex, and scanner model. We validated AD-NeuroScore using 929 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, with a mean age of 72.7 years (SD = 6.3; 55.1-91.5) and cognitively normal (CN), mild cognitive impairment (MCI), or AD diagnoses. Our validation results showed that AD-NeuroScore was significantly associated with diagnosis and disease severity scores (measured by MMSE, CDR-SB, and ADAS-11) at baseline. Furthermore, baseline AD-NeuroScore was associated with both changes in diagnosis and disease severity scores at all time points with available data. The performance of AD-NeuroScore was equivalent or superior to adjusted hippocampal volume (AHV), a widely used metric in AD research. Further, AD-NeuroScore typically performed as well as or sometimes better when compared to other existing sMRI-based metrics. In conclusion, we have introduced a new metric, AD-NeuroScore, which shows promising results in detecting AD, benchmarking disease severity, and predicting disease progression. AD-NeuroScore differentiates itself from other metrics by being clinically practical and interpretable.

Cortical atrophy and leukoaraiosis, imaging markers of cerebrovascular small vessel disease, are associated with driving behavior changes among cognitively normal older adults

BACKGROUND

Cerebral small vessel disease (CSVD) as measured by cortical atrophy and white matter hyperintensities [leukoaraiosis], captured via magnetic resonance imaging (MRI) are increasing in prevalence due to the growth of the aging population and an increase in cardiovascular risk factors in the population. CSVD impacts cognitive function and mobility, but it is unclear if it affects complex, functional activities like driving.

METHODS

In a cohort of 163 cognitively normal, community-dwelling older adults (age ≥ 65), we compared naturalistic driving behavior with mild/moderate leukoaraiosis, cortical atrophy, or their combined rating in a clinical composite termed, aging-related changes to those without any, over a two-and-a-half-year period.

RESULTS

Older drivers with mild or moderate cortical atrophy and aging-related changes (composite) experienced a greater decrease in the number of monthly trips which was due to a decrease in the number of trips made within a one-to-five-mile diameter from their residence. Older drivers with CSVD experience a larger reduction in daily driving behaviors than drivers without CSVD, which may serve as an early neurobehavioral marker for functional decline.

CONCLUSIONS

As CSVD markers, leukoaraiosis and cortical atrophy are standard MRI metrics that are widely available and can be used for screening individuals at higher risk for driving safety risk and decline in community mobility.

Prospective Longitudinal Perfusion in Probable Alzheimer's Disease Correlated with Atrophy in Temporal Lobe

Reduced cerebral blood flow (CBF) in the temporoparietal region and gray matter volumes (GMVs) in the temporal lobe were previously reported in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the temporal relationship between reductions in CBF and GMVs requires further investigation. This study sought to determine if reduced CBF is associated with reduced GMVs, or vice versa. Data came from 148 volunteers of the Cardiovascular Health Study Cognition Study (CHS-CS), including 58 normal controls (NC), 50 MCI, and 40 AD who had perfusion and structural MRIs during 2002-2003 (Time 2). Sixty-three of the 148 volunteers had follow-up perfusion and structural MRIs (Time 3). Forty out of the 63 volunteers received prior structural MRIs during 1997-1999 (Time 1). The relationships between GMVs and subsequent CBF changes, and between CBF and subsequent GMV changes were investigated. At Time 2, we observed smaller GMVs (p<0.05) in the temporal pole region in AD compared to NC and MCI. We also found associations between: (1) temporal pole GMVs at Time 2 and subsequent declines in CBF in this region (p=0.0014) and in the temporoparietal region (p=0.0032); (2) hippocampal GMVs at Time 2 and subsequent declines in CBF in the temporoparietal region (p=0.012); and (3) temporal pole CBF at Time 2 and subsequent changes in GMV in this region (p = 0.011). Therefore, hypoperfusion in the temporal pole may be an early event driving its atrophy. Perfusion declines in the temporoparietal and temporal pole follow atrophy in this temporal pole region.

Childhood obesity is linked to putative neuroinflammation in brain white matter, hypothalamus, and striatum

Neuroinflammation is both a consequence and driver of overfeeding and weight gain in rodent obesity models. Advances in magnetic resonance imaging (MRI) enable investigations of brain microstructure that suggests neuroinflammation in human obesity. To assess the convergent validity across MRI techniques and extend previous findings, we used diffusion basis spectrum imaging (DBSI) to characterize obesity-associated alterations in brain microstructure in 601 children (age 9-11 years) from the Adolescent Brain Cognitive DevelopmentSM Study. Compared with children with normal-weight, greater DBSI restricted fraction (RF), reflecting neuroinflammation-related cellularity, was seen in widespread white matter in children with overweight and obesity. Greater DBSI-RF in hypothalamus, caudate nucleus, putamen, and, in particular, nucleus accumbens, correlated with higher baseline body mass index and related anthropometrics. Comparable findings were seen in the striatum with a previously reported restriction spectrum imaging (RSI) model. Gain in waist circumference over 1 and 2 years related, at nominal significance, to greater baseline RSI-assessed restricted diffusion in nucleus accumbens and caudate nucleus, and DBSI-RF in hypothalamus, respectively. Here we demonstrate that childhood obesity is associated with microstructural alterations in white matter, hypothalamus, and striatum. Our results also support the reproducibility, across MRI methods, of findings of obesity-related putative neuroinflammation in children.

A flexible modeling approach for biomarker-based computation of absolute risk of Alzheimer's disease dementia

INTRODUCTION

As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia.

METHODS

We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis.

RESULTS

A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC = 0.79), and apolipoprotein E genotype (AUC = 0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC = 0.84), and for plasma amyloid beta (Aβ)42/Aβ40 (AUC = 0.82).

DISCUSSION

An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults.

Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms

BACKGROUND AND PURPOSE

Automated volumetric analysis of structural MR imaging allows quantitative assessment of brain atrophy in neurodegenerative disorders. We compared the brain segmentation performance of the AI-Rad Companion brain MR imaging software against an in-house FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline.

MATERIALS AND METHODS

T1-weighted images of 45 participants with de novo memory symptoms were selected from the OASIS-4 database and analyzed through the AI-Rad Companion brain MR imaging tool and the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. Correlation, agreement, and consistency between the 2 tools were compared among the absolute, normalized, and standardized volumes. Final reports generated by each tool were used to compare the rates of detection of abnormality and the compatibility of radiologic impressions made using each tool, compared with the clinical diagnoses.

RESULTS

We observed strong correlation, moderate consistency, and poor agreement between absolute volumes of the main cortical lobes and subcortical structures measured by the AI-Rad Companion brain MR imaging tool compared with FreeSurfer. The strength of the correlations increased after normalizing the measurements to the total intracranial volume. Standardized measurements differed significantly between the 2 tools, likely owing to differences in the normative data sets used to calibrate each tool. When considering the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline as a reference standard, the AI-Rad Companion brain MR imaging tool had a specificity of 90.6%-100% and a sensitivity of 64.3%-100% in detecting volumetric abnormalities. There was no difference between the rate of compatibility of radiologic and clinical impressions when using the 2 tools.

CONCLUSIONS

The AI-Rad Companion brain MR imaging tool reliably detects atrophy in cortical and subcortical regions implicated in the differential diagnosis of dementia.

Brain PET Imaging: Frontotemporal Dementia

Brain PET adds value in diagnosing neurodegenerative disorders, especially frontotemporal dementia (FTD) due to its syndromic presentation that overlaps with a variety of other neurodegenerative and psychiatric disorders. 18F-FDG-PET has improved sensitivity and specificity compared with structural MR imaging, with optimal diagnostic results achieved when both techniques are utilized. PET demonstrates superior sensitivity compared with SPECT for FTD diagnosis that is primarily a supplement to other imaging and clinical evaluations. Tau-PET and amyloid-PET primary use in FTD diagnosis is differentiation from Alzheimer disease, although these methods are limited mainly to research settings.

Longitudinal Patterns of Brain Changes in a Community Sample in Relation to Aging and Cognitive Status

BACKGROUND

Aging and Alzheimer's disease (AD) are characterized by widespread cortical and subcortical atrophy. Though atrophy patterns between aging and AD overlap considerably, regional differences between these two conditions may exist. Few studies, however, have investigated these patterns in large community samples.

OBJECTIVE

Elaborate longitudinal changes in brain morphometry in relation to aging and cognitive status in a well-characterized community cohort.

METHODS

Clinical and neuroimaging data were compiled from 72 participants from the Cardiovascular Health Study-Cognition Study, a community cohort of healthy aging and probable AD participants. Two time points were identified for each participant with a mean follow-up time of 5.36 years. MRI post-processing, morphometric measurements, and statistical analyses were performed using FreeSurfer, Version 7.1.1.

RESULTS

Cortical volume was significantly decreased in the bilateral superior frontal, bilateral inferior parietal, and left superior parietal regions, among others. Cortical thickness was significantly reduced in the bilateral superior frontal and left inferior parietal regions, among others. Overall gray and white matter volumes and hippocampal subfields also demonstrated significant reductions. Cortical volume atrophy trajectories between cognitively stable and cognitively declined participants were significantly different in the right postcentral region.

CONCLUSION

Observed volume reductions were consistent with previous studies investigating morphometric brain changes. Patterns of brain atrophy between AD and aging may be different in magnitude but exhibit widespread spatial overlap. These findings help characterize patterns of brain atrophy that may reflect the general population. Larger studies may more definitively establish population norms of aging and AD-related neuroimaging changes.

Paving the Way for Alzheimer's Disease Prevention: A Systematic Review of Global Open-Access Neuroimaging Datasets in Healthy Individuals

BACKGROUND

Given the advent of large-scale neuroimaging data-driven endeavors for Alzheimer's disease, there is a burgeoning need for well-characterized neuroimaging databases of healthy individuals. With the rise of initiatives around the globe for the rapid and unrestricted sharing of data resources, there is now an abundance of open-source neuroimaging datasets available to the research community. However, there is not yet a systematic review that fully details the demographic information and modalities actually available in all open access neuroimaging databases around the globe.

OBJECTIVE

This systematic review aims to provide compile a list of MR structural imaging databases encompassing healthy individuals across the lifespan.

METHODS

In this systematic review, we searched EMBASE and PubMed until May 2022 for open-access neuroimaging databases containing healthy control participants of any age, race, with normal development and cognition having at least one structural T1-weighted neuroimaging scan.

RESULTS

A total of 403 databases were included, for up to total of 48,268 participants with all available demographic information and imaging modalities detailed in Supplementary Table 1. There were significant trends noted when compiling normative databases for this systematic review, notably that 11.7% of databases included reported ethnicity in their participants, with underrepresentation of many socioeconomic groups globally.

CONCLUSIONS

As efforts to improve primary prevention of AD may require a broader perspective including increased relevance of earlier stages in life, and strategies in addressing modifiable risk factors may be individualized to specific demographics, improving data characterization to be richer and more rigorous will greatly enhance these efforts.

Handgrip Strength Is Related to Hippocampal and Lobar Brain Volumes in a Cohort of Cognitively Impaired Older Adults with Confirmed Amyloid Burden

BACKGROUND

Strength and mobility are essential for activities of daily living. With aging, weaker handgrip strength, mobility, and asymmetry predict poorer cognition. We therefore sought to quantify the relationship between handgrip metrics and volumes quantified on brain magnetic resonance imaging (MRI).

OBJECTIVE

To model the relationships between handgrip strength, mobility, and MRI volumetry.

METHODS

We selected 38 participants with Alzheimer's disease dementia: biomarker evidence of amyloidosis and impaired cognition. Handgrip strength on dominant and non-dominant hands was measured with a hand dynamometer. Handgrip asymmetry was calculated. Two-minute walk test (2MWT) mobility evaluation was combined with handgrip strength to identify non-frail versus frail persons. Brain MRI volumes were quantified with Neuroreader. Multiple regression adjusting for age, sex, education, handedness, body mass index, and head size modeled handgrip strength, asymmetry and 2MWT with brain volumes. We modeled non-frail versus frail status relationships with brain structures by analysis of covariance.

RESULTS

Higher non-dominant handgrip strength was associated with larger volumes in the hippocampus (p = 0.02). Dominant handgrip strength was related to higher frontal lobe volumes (p = 0.02). Higher 2MWT scores were associated with larger hippocampal (p = 0.04), frontal (p = 0.01), temporal (p = 0.03), parietal (p = 0.009), and occipital lobe (p = 0.005) volumes. Frailty was associated with reduced frontal, temporal, and parietal lobe volumes.

CONCLUSION

Greater handgrip strength and mobility were related to larger hippocampal and lobar brain volumes. Interventions focused on improving handgrip strength and mobility may seek to include quantified brain volumes on MR imaging as endpoints.

Longitudinal White and Gray Matter Response to Precision Medicine-Guided Intervention for Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a debilitating condition that is widely known to adversely affect gray matter (GM) and white matter (WM) tracts within the brain. Recently, precision medicine has shown promise in alleviating the clinical and gross morphological trajectories of patients with AD. However, regional morphological changes have not yet been adequately characterized.

OBJECTIVE

Investigate regional morphological responses to a precision medicine-guided intervention with regards to white and gray matter in AD and mild cognitive impairment (MCI).

METHODS

Clinical and neuroimaging data were compiled over a 9-month period from 25 individuals who were diagnosed with AD or MCI receiving individualized treatment plans. Structural T1-weighted MRI scans underwent segmentation and volumetric quantifications via Neuroreader. Longitudinal changes were calculated via annualized percent change of WM or GM ratios.

RESULTS

Montreal Cognitive Assessment scores (p < 0.001) and various domains of the Computerized Neurocognitive Screening Vital Signs significantly improved from baseline to 9-month follow-up. There was regional variability in WM and GM atrophy or hypertrophy, but none of these observed changes were statistically significant after correction for multiple comparisons.

Impact of Eating a Carbohydrate-Restricted Diet on Cortical Atrophy in a Cross-Section of Amyloid Positive Patients with Alzheimer's Disease: A Small Sample Study

BACKGROUND

A carbohydrate-restricted diet aimed at lowering insulin levels has the potential to slow Alzheimer's disease (AD). Restricting carbohydrate consumption reduces insulin resistance, which could improve glucose uptake and neural health. A hallmark feature of AD is widespread cortical thinning; however, no study has demonstrated that lower net carbohydrate (nCHO) intake is linked to attenuated cortical atrophy in patients with AD and confirmed amyloidosis.

OBJECTIVE

We tested the hypothesis that individuals with AD and confirmed amyloid burden eating a carbohydrate-restricted diet have thicker cortex than those eating a moderate-to-high carbohydrate diet.

METHODS

A total of 31 patients (mean age 71.4±7.0 years) with AD and confirmed amyloid burden were divided into two groups based on a 130 g/day nCHO cutoff. Cortical thickness was estimated from T1-weighted MRI using FreeSurfer. Cortical surface analyses were corrected for multiple comparisons using cluster-wise probability. We assessed group differences using a two-tailed two-independent sample t-test. Linear regression analyses using nCHO as a continuous variable, accounting for confounders, were also conducted.

RESULTS

The lower nCHO group had significantly thicker cortex within somatomotor and visual networks. Linear regression analysis revealed that lower nCHO intake levels had a significant association with cortical thickness within the frontoparietal, cingulo-opercular, and visual networks.

CONCLUSIONS

Restricting carbohydrates may be associated with reduced atrophy in patients with AD. Lowering nCHO to under 130 g/day would allow patients to follow the well-validated MIND diet while benefiting from lower insulin levels.

Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease

BACKGROUND

Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology.

OBJECTIVE

To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS.

METHODS

We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging.

RESULTS

After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003).

CONCLUSION

These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.

Amyloid-Related Imaging Abnormalities with Emerging Alzheimer Disease Therapeutics: Detection and Reporting Recommendations for Clinical Practice

Monoclonal antibodies are emerging disease-modifying therapies for Alzheimer disease that require brain MR imaging for eligibility assessment as well as for monitoring for amyloid-related imaging abnormalities. Amyloid-related imaging abnormalities result from treatment-related loss of vascular integrity and may occur in 2 forms. Amyloid-related imaging abnormalities with edema or effusion are transient, treatment-induced edema or sulcal effusion, identified on T2-FLAIR. Amyloid-related imaging abnormalities with hemorrhage are treatment-induced microhemorrhages or superficial siderosis identified on T2* gradient recalled-echo. As monoclonal antibodies become more widely available, treatment screening and monitoring brain MR imaging examinations may greatly increase neuroradiology practice volumes. Radiologists must become familiar with the imaging appearance of amyloid-related imaging abnormalities, how to select an appropriate imaging protocol, and report findings in clinical practice. On the basis of clinical trial literature and expert experience from clinical trial imaging, we summarize imaging findings of amyloid-related imaging abnormalities, describe potential interpretation pitfalls, and provide recommendations for a standardized imaging protocol and an amyloid-related imaging abnormalities reporting template. Standardized imaging and reporting of these findings are important because an amyloid-related imaging abnormalities severity score, derived from the imaging findings, is used along with clinical status to determine patient management and eligibility for continued monoclonal antibody dosing.

The Value of Neuroimaging in Dementia Diagnosis

PURPOSE OF REVIEW

This article discusses neuroimaging in dementia diagnosis, with a focus on new applications of MRI and positron emission tomography (PET).

RECENT FINDINGS

Although the historical use of MRI in dementia diagnosis has been supportive to exclude structural etiologies, recent innovations allow for quantification of atrophy patterns that improve sensitivity for supporting the diagnosis of dementia causes. Neuronuclear approaches allow for localization of specific amyloid and tau neuropathology on PET and are available for clinical use, in addition to dopamine transporter scans in dementia with Lewy bodies and metabolic studies with fludeoxyglucose PET (FDG-PET).

SUMMARY

Using computerized software programs for MRI analysis and cross-sectional and longitudinal evaluations of hippocampal, ventricular, and lobar volumes improves sensitivity in support of the diagnosis of Alzheimer disease and frontotemporal dementia. MRI protocol requirements for such quantification are three-dimensional T1-weighted volumetric imaging protocols, which may need to be specifically requested. Fluid-attenuated inversion recovery (FLAIR) and 3.0T susceptibility-weighted imaging (SWI) sequences are useful for the detection of white matter hyperintensities as well as microhemorrhages in vascular dementia and cerebral amyloid angiopathy. PET studies for amyloid and/or tau pathology can add additional specificity to the diagnosis but currently remain largely inaccessible outside of research settings because of prohibitive cost constraints in most of the world. Dopamine transporter PET scans can help identify Lewy body dementia and are thus of potential clinical value.

Sex-Specific Patterns of Body Mass Index Relationship with White Matter Connectivity

BACKGROUND

Obesity is an increasingly recognized modifiable risk factor for Alzheimer's disease (AD). Increased body mass index (BMI) is related to distinct changes in white matter (WM) fiber density and connectivity.

OBJECTIVE

We investigated whether sex differentially affects the relationship between BMI and WM structural connectivity.

METHODS

A cross-sectional sample of 231 cognitively normal participants were enrolled from the Knight Alzheimer Disease Research Center. Connectome analyses were done with diffusion data reconstructed using q-space diffeomorphic reconstruction to obtain the spin distribution function and tracts were selected using a deterministic fiber tracking algorithm.

RESULTS

We identified an inverse relationship between higher BMI and lower connectivity in the associational fibers of the temporal lobe in overweight and obese men. Normal to overweight women showed a significant positive association between BMI and connectivity in a wide array of WM fibers, an association that reversed in obese and morbidly obese women. Interaction analyses revealed that with increasing BMI, women showed higher WM connectivity in the bilateral frontoparietal and parahippocampal parts of the cingulum, while men showed lower connectivity in right sided corticostriatal and corticopontine tracts. Subgroup analyses demonstrated comparable results in participants with and without positron emission tomography or cerebrospinal fluid evidence of brain amyloidosis, indicating that the relationship between BMI and structural connectivity in men and women is independent of AD biomarker status.

CONCLUSION

BMI influences structural connectivity of WM differently in men and women across BMI categories and this relationship does not vary as a function of preclinical AD.

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease

BACKGROUND

The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias.

OBJECTIVE

To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD.

METHODS

3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions.

RESULTS

Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis.

CONCLUSION

Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span

BACKGROUND AND PURPOSE

The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.

MATERIALS AND METHODS

We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults (n = 176, 89 women) across a wide age range (20-79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.

RESULTS

Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated (r = 0.93 and 0.9, respectively; both P < .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P < .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.

CONCLUSIONS

The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.

Optimizing Use of Neuroimaging Tools in Evaluation of Prodromal Alzheimer's Disease and Related Disorders

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by preclinical, pre-dementia, and dementia phases. Progression of the disease leads to cognitive decline and is associated with loss of functional independence, personality changes, and behavioral disturbances. Current guidelines for AD diagnosis include the use of neuroimaging tools as biomarkers for identifying and monitoring pathological changes. Various imaging modalities, namely magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET) and PET with amyloid-beta tracers are available to facilitate early accurate diagnoses. Enhancing diagnosis in the early stages of the disease can allow for timely interventions that can delay progression of the disease. This paper will discuss the characteristic findings associated with each of the imaging tools for patients with AD, with a focus on FDG-PET due to its established accuracy in assisting with the differential diagnosis of dementia and discussion of other methods including MRI. Diagnostically-relevant features to aid clinicians in making a differential diagnosis will also be pointed out and multimodal imaging will be reviewed. We also discuss the role of quantification software in interpretation of brain imaging. Lastly, to guide evaluation of patients presenting with cognitive deficits, an algorithm for optimal integration of these imaging tools will be shared. Molecular imaging modalities used in dementia evaluations hold promise toward identifying AD-related pathology before symptoms are fully in evidence. The work describes state of the art functional and molecular imaging methods for AD. It will also overview a clinically applicable quantitative method for reproducible assessments of such scans in the early identification of AD.

Nucleus accumbens microstructure mediates the relationship between obesity and eating behavior in adults

OBJECTIVE

Basal ganglia regions are part of the brain's reward-processing networks and are implicated in the neurobiology of obesity and eating disorders. This study examines basal ganglia microstructural properties in adults with and without obesity.

METHODS

Diffusion basis spectrum imaging (DBSI) images were analyzed to obtain putative imaging markers of neuroinflammation. Relationships between basal ganglia DBSI metrics and reward sensitivity and eating behaviors were also explored.

RESULTS

A total of 46 participants (25 people with obesity; aged 20-40 years; 37 women) were included. Relative to the people in the normal-weight group, people with obesity had smaller caudate and larger nucleus accumbens (NAcc) volumes (p < 0.05) and lower DBSI fiber fraction (reflecting apparent axonal/dendrite density) in NAcc and putamen, higher DBSI nonrestricted fraction (reflecting tissue edema) in NAcc and caudate, and higher DBSI restricted fraction (reflecting tissue cellularity) in putamen (p ≤ 0.01, all). Increased emotional and reward eating behaviors were related to lower NAcc axonal/dendrite density and greater tissue edema (p ≤ 0.002). The relationships between emotional eating and adiposity measures were mediated by NAcc microstructure.

CONCLUSIONS

These findings provide evidence that microstructural alterations in basal ganglia relate to obesity and insights linking NAcc microstructure and eating behavior in adults.

Obesity and White Matter Neuroinflammation Related Edema in Alzheimer's Disease Dementia Biomarker Negative Cognitively Normal Individuals

BACKGROUND

Obesity is related to quantitative neuroimaging abnormalities including reduced gray matter volumes and impaired white matter microstructural integrity, although the underlying mechanisms are not well understood.

OBJECTIVE

We assessed influence of obesity on neuroinflammation imaging that may mediate brain morphometric changes. Establishing the role of neuroinflammation in obesity will enhance understanding of this modifiable disorder as a risk factor for Alzheimer's disease (AD) dementia.

METHODS

We analyzed brain MRIs from 104 cognitively normal participants (CDR = 0) and biomarker negativity for CSF amyloid or tau. We classified body mass index (BMI) as normal (BMI <25, N = 62) or overweight and obese (BMI ≥25, N = 42). Blood pressure was measured. BMI and blood pressure classifications were related to neuroinflammation imaging (NII) derived edema fraction in 17 white matter tracts. This metric was also correlated to hippocampal volumes and CSF biomarkers of inflammation and neurodegeneration: YKL-40, SNAP25, VILIP, tau, and NFL.

RESULTS

Participants with BMI <25 had lower NII-derived edema fraction, with protective effects of normal blood pressure. Statistically significant white matter tracts included the internal capsule, external capsule, and corona radiata, FDR correc-ted for multiple comparisons to alpha = 0.05. Higher NII-derived edema fractions in the internal capsule, corpus callosum, gyrus, and superior fronto-occipital fasciculus were related with smaller hippocampal volumes only in individuals with BMI ≥25. There were no statistically significant correlations between NII-derived edema fraction and CSF biomarkers.

CONCLUSION

We demonstrate statistically significant relationships between neuroinflammation, elevated BMI, and hippocampal volume, raising implications for neuroinflammation mechanisms of obesity-related brain dysfunction in cognitively normal elderly.

Estrogen, brain structure, and cognition in postmenopausal women

Declining estrogen levels before, during, and after menopause can affect memory and risk for Alzheimer's disease. Undesirable side effects of hormone variations emphasize a role for hormone therapy (HT) where possible benefits include a delay in the onset of dementia-yet findings are inconsistent. Effects of HT may be mediated by estrogen receptors found throughout the brain. Effects may also depend on lifestyle factors, timing of use, and genetic risk. We studied the impact of self-reported HT use on brain volume in 562 elderly women (71-94 years) with mixed cognitive status while adjusting for aforementioned factors. Covariate-adjusted voxelwise linear regression analyses using a model with 16 predictors showed HT use as positively associated with regional brain volumes, regardless of cognitive status. Examinations of other factors related to menopause, oophorectomy and hysterectomy status independently yielded positive effects on brain volume when added to our model. One interaction term, HTxBMI, out of several examined, revealed significant negative association with overall brain volume, suggesting a greater reduction in brain volume than BMI alone. Our main findings relating HT to regional brain volume were as hypothesized, but some exploratory analyses were not in line with existing hypotheses. Studies suggest lower levels of estrogen resulting from oophorectomy and hysterectomy affect brain volume negatively, and the addition of HT modifies the relation between BMI and brain volume positively. Effects of HT may depend on the age range assessed, motivating studies with a wider age range as well as a randomized design.

Quantitative MRI Differences Between Early versus Late Onset Alzheimer's Disease

Investigators report greater parietal tau deposition and alternate frontoparietal network involvement in early onset Alzheimer's Disease (EOAD) with onset <65 years as compared with typical late onset AD (LOAD). To determine whether clinical brain MRI volumes reflect these differences in EOAD compared with LOAD. This study investigated the clinical MRI scans of 45 persons with Clinically Probable AD with onset <65 years, and compared them to 32 with Clinically Probable AD with onset ≥65 years. Brain volumes on their T1 MRI scans were quantified with a volumetric program. Receiver operating curve analyses were performed. Persons with EOAD had significantly smaller parietal lobes (volumetric percentiles) than LOAD. Late onset Alzheimer's Disease had a smaller left putamen and hippocampus. Area Under the Curve was 96.5% with brain region delineation of EOAD compared to LOAD. This study indicates parietal atrophy less than 30% of normal on clinical MRI scans is suggestive of EOAD compared to LOAD.

MRI Volumetric Quantification in Persons with a History of Traumatic Brain Injury and Cognitive Impairment

BACKGROUND

While traumatic brain injury (TBI) is recognized as a risk factor for dementia, there is lack of clinical tools to identify brain changes that may confer such vulnerability. Brain MRI volumetric quantification can sensitively identify brain atrophy.

OBJECTIVE

To characterize regional brain volume loss in persons with TBI presenting with cognitive impairment.

METHODS

IRB approved review of medical records in patients with cognitive decline focused on those who had documented TBI histories and brain MRI scans after TBI (n = 40, 67.7±14.5 years) with volumetric quantification by applying an FDA cleared software program. TBI documentation included head trauma mechanism. Brain volumes were compared to a normative database to determine the extent of atrophy. Correlations between these regions and global tests of cognition (MMSE in n = 17, MoCA in n = 27, n = 14 in both) were performed.

RESULTS

Multiple regions demonstrated volume loss in TBI, particularly ventral diencephalon, putamen, and pallidum with smaller magnitude of atrophy in temporal lobes and brainstem. Lobar structures showed strongest correlations between atrophy and lower scores on MMSE and MoCA. The hippocampus, while correlated to tests of cognitive function, was the least atrophic region as a function of TBI history.

CONCLUSION

Persons with TBI history exhibit show regional brain atrophy. Several of these areas, such as thalamus and temporal lobes, also correlate with cognitive function. Alzheimer's disease atrophy was less likely given relative sparing of the hippocampi. Volumetric quantification of brain MRI in TBI warrants further investigation to further determine its clinical potential in TBI and differentiating causes of cognitive impairment.

Going against the norm: validation of a novel alternative to brain SPECT normative datasets

Aim: Quantitative analysis of brain single photon emission computed tomography (SPECT) perfusion imaging is dependent on normative datasets that are challenging to produce. This study investigated the combination of SPECT neuroimaging from a large clinical population rather than small numbers of controls. The authors hypothesized this “population template” would demonstrate noninferiority to a control dataset, providing a viable alternative for quantifying perfusion abnormalities in SPECT neuroimaging. Methods: A total of 2, 068 clinical SPECT scans were averaged to form the “population template”. Validation was three-fold. First, the template was imported into SPECT brain analysis software, MIMneuro®, and compared against its control dataset of 90 individuals through its region and cluster analysis tools. Second, a cohort of 100 cognitively impaired subjects was evaluated against both the population template and MIMneuro®’s normative dataset to compute region-based metrics. Concordance and intraclass correlation coefficients, mean square deviations, total deviation indices, and limits of agreement were derived from these data to measure agreement and test for noninferiority. Finally, the same patients were clinically read in CereMetrix® to confirm that expected perfusion patterns appeared after comparison to the template. Results: MIMneuro®’s default threshold for normality is ± 1.65 z-score and this served as our noninferiority margin. Direct comparison of the template to controls produced no regions that exceeded this threshold and all clusters identified were far from statistically significant. Agreement measures revealed consistency between the softwares and that CereMetrix® results were noninferior to MIMneuro®, albeit with proportional bias. Visual analysis also confirmed that expected perfusion patterns appeared when individual scans were compared to the population template within CereMetrix®. Conclusions: The authors demonstrated a population template was noninferior to a smaller control dataset despite inclusion of abnormal scans. This suggests that our patient-based population template can serve as an alternative for identifying and quantifying perfusion abnormalities in brain SPECT.

Brain Structure in Bilingual Compared to Monolingual Individuals with Alzheimer's Disease: Proof of Concept

BACKGROUND

Bilingualism is increasingly recognized as protective in persons at risk for Alzheimer's disease (AD).

OBJECTIVE

Compare MRI measured brain volumes in matched bilinguals versus monolinguals with AD.

METHODS

This IRB approved study analyzed T1 volumetric brain MRIs of patients with criteria-supported Probable AD. We identified 17 sequential bilinguals (any native language) with Probable AD, matched to 28 (62%) monolinguals on age and MMSE. Brain volumes were quantified with Neuroreader. Regional volumes as fraction of total intracranial volume (TIV) were compared between both groups, and Cohen's D effect sizes were calculated for statistically significant structures. Partial correlations between bilingualism and brain volumes adjusted for age, gender, and TIV.

RESULTS

Bilinguals had higher brain volumes in 37 structures. Statistical significance (p < 0.05) was observed in brainstem (t = 2.33, p = 0.02, Cohen's D = 0.71) and ventral diencephalon (t = 3.01, p = 0.004, Cohen's D = 0.91). Partial correlations showed statistical significance between bilingualism and larger volumes in brainstem (rp = 0 . 37, p = 0.01), thalamus (rp = 0.31, p = 0.04), ventral diencephalon (rp = 0.50, p = 0.001), and pallidum (rp = 0.38, p = 0.01). Bilingualism positively correlated with hippocampal volume, though not statistically significant (rp = 0.17, p = 0.26). No brain volumes were larger in monolinguals.

CONCLUSION

Bilinguals demonstrated larger thalamic, ventral diencephalon, and brainstem volumes compared to matched monolinguals with AD. This may represent a neural substrate for increased cognitive reserve in bilingualism. Future studies should extrapolate this finding into cognitively normal persons at risk for AD.

Select Atrophied Regions in Alzheimer disease (SARA): An improved volumetric model for identifying Alzheimer disease dementia

INTRODUCTION

Volumetric biomarkers for Alzheimer disease (AD) are attractive due to their wide availability and ease of administration, but have traditionally shown lower diagnostic accuracy than measures of neuropathological contributors to AD. Our purpose was to optimize the diagnostic specificity of structural MRIs for AD using quantitative, data-driven techniques.

METHODS

This retrospective study assembled several non-overlapping cohorts (total n = 1287) with publicly available data and clinical patients from Barnes-Jewish Hospital (data gathered 1990-2018). The Normal Aging Cohort (n = 383) contained amyloid biomarker negative, cognitively normal (CN) participants, and provided a basis for determining age-related atrophy in other cohorts. The Training (n = 216) and Test (n = 109) Cohorts contained participants with symptomatic AD and CN controls. Classification models were developed in the Training Cohort and compared in the Test Cohort using the receiver operating characteristics areas under curve (AUCs). Additional model comparisons were done in the Clinical Cohort (n = 579), which contained patients who were diagnosed with dementia due to various etiologies in a tertiary care outpatient memory clinic.

RESULTS

While the Normal Aging Cohort showed regional age-related atrophy, classification models were not improved by including age as a predictor or by using volumetrics adjusted for age-related atrophy. The optimal model used multiple regions (hippocampal volume, inferior lateral ventricle volume, amygdala volume, entorhinal thickness, and inferior parietal thickness) and was able to separate AD and CN controls in the Test Cohort with an AUC of 0.961. In the Clinical Cohort, this model separated AD from non-AD diagnoses with an AUC 0.820, an incrementally greater separation of the cohort than by hippocampal volume alone (AUC of 0.801, p = 0.06). Greatest separation was seen for AD vs. frontotemporal dementia and for AD vs. non-neurodegenerative diagnoses.

CONCLUSIONS

Volumetric biomarkers distinguished individuals with symptomatic AD from CN controls and other dementia types but were not improved by controlling for normal aging.

Neurobiology of COVID-19

Anosmia, stroke, paralysis, cranial nerve deficits, encephalopathy, delirium, meningitis, and seizures are some of the neurological complications in patients with coronavirus disease-19 (COVID-19) which is caused by acute respiratory syndrome coronavirus 2 (SARS-Cov2). There remains a challenge to determine the extent to which neurological abnormalities in COVID-19 are caused by SARS-Cov2 itself, the exaggerated cytokine response it triggers, and/or the resulting hypercoagulapathy and formation of blood clots in blood vessels throughout the body and the brain. In this article, we review the reports that address neurological manifestations in patients with COVID-19 who may present with acute neurological symptoms (e.g., stroke), even without typical respiratory symptoms such as fever, cough, or shortness of breath. Next, we discuss the different neurobiological processes and mechanisms that may underlie the link between SARS-Cov2 and COVID-19 in the brain, cranial nerves, peripheral nerves, and muscles. Finally, we propose a basic "NeuroCovid" classification scheme that integrates these concepts and highlights some of the short-term challenges for the practice of neurology today and the long-term sequalae of COVID-19 such as depression, OCD, insomnia, cognitive decline, accelerated aging, Parkinson's disease, or Alzheimer's disease in the future. In doing so, we intend to provide a basis from which to build on future hypotheses and investigations regarding SARS-Cov2 and the nervous system.

Overview of MR Imaging Volumetric Quantification in Neurocognitive Disorders

This review article provides a general overview on the various methodologies for quantifying brain structure on magnetic resonance images of the human brain. This overview is followed by examples of applications in Alzheimer dementia and mild cognitive impairment. Other examples will include traumatic brain injury and other neurodegenerative dementias. Finally, an overview of general principles for protocol acquisition of magnetic resonance imaging for volumetric quantification will be discussed along with the current choices of FDA cleared algorithms for use in clinical practice.

Patterns of Regional Cerebral Blood Flow as a Function of Age Throughout the Lifespan

BACKGROUND

Understanding the influence of aging on the brain remains a challenge in determining its role as a risk factor for Alzheimer's disease.

OBJECTIVE

To identify patterns of aging in a large neuroimaging cohort.

METHODS

A large psychiatric cohort of 31,227 individuals received brain SPECT at rest and during a concentration task for a total of 62,454 scans. ANOVA was done to identify the mean age trends over the course of the age range in this group, 0-105 years. A regression model in which brain SPECT regions of interest was used to predict chronological age (CA) was then utilized to derive brain estimated age (BEA). The difference between CA and BEA was calculated to determine increased brain aging in common disorders in our sample such as depression, dementia, substance use, and anxiety.

RESULTS

Throughout the lifespan, variations in perfusion were observed in childhood, adolescence, and late life. Increased brain aging was seen in alcohol use, cannabis use, anxiety, bipolar, schizophrenia, attention-deficit/hyperactivity disorder, and in men.

CONCLUSION

Brain SPECT can predict chronological age and this feature varies as a function of common psychiatric disorders.

Emerging advances of in vivo detection of chronic traumatic encephalopathy and traumatic brain injury

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder that is of epidemic proportions in contact sports athletes and is linked to subconcussive and concussive repetitive head impacts (RHI). Although postmortem analysis is currently the only confirmatory method to diagnose CTE, there has been progress in early detection techniques of fluid biomarkers as well as in advanced neuroimaging techniques. Specifically, promising new methods of diffusion MRI and radionucleotide PET scans could aid in the early detection of CTE.The authors examine early detection methods focusing on various neuroimaging techniques. Advances in structural and diffusion MRI have demonstrated the ability to measure volumetric and white matter abnormalities associated with CTE. Recent studies using radionucleotides such as flortaucipir and ¹⁸F-FDDNP have shown binding patterns that are consistent with the four stages of neurofibrillary tangle (NFT) distribution postmortem. Additional research undertakings focusing on fMRI, MR spectroscopy, susceptibility-weighted imaging, and singlephoton emission CT are also discussed as are advanced MRI methods such as diffusiontensor imaging and arterial spin labeled. Neuroimaging is fast becoming a key instrument in early detection and could prove essential for CTE quantification. This review explores a global approach to in vivo early detection.Limited data of in vivo CTE biomarkers with postmortem confirmation are available. While some data exist, they are limited by selection bias. It is unlikely that a single test will be sufficient to properly diagnosis and distinguish CTE from other neurodegenerative diseases such as Alzheimer disease or Frontotemporal Dementia. However, with a combination of fluid biomarkers, neuroimaging, and genetic testing, early detection may become possible.